A Robust Optimization Approach for Uncertainty Management of Smart Water and Energy Hub along with Demand Response Program

Energy and water are two important factors that are crucial for human survival. In an energy hub, integrated management of water and multi-type of energies such as electrical power, gas, and thermal power increases the economic efficiency of using vital resources. One of the major challenges that deter the effectiveness of this integrated management is the electricity price uncertainties of the upstream market. To address this problem, this paper provides a novel mathematical model along with a robust optimization approach for uncertainty management in smart water and energy hubs. In the proposed robust uncertainty approach, the objective function is optimized subject to the uncertainty set of the problem. Therefore, the optimal solution of the proposed optimization problem is an effective point referring to the amount of specified uncertainty budget by the energy hub system operator. Moreover, a new water infrastructure including a water desalination system and water storage is considered in the proposed smart water and energy hubs. The proposed power and water robust optimization (PWRO) is a Mixed Integer Linear Programing (MILP) model and is solved by CPLEX solver in GAMS environment. The effectiveness of the proposed approach is examined in a case study. Results show that the operation cost of the proposed model increases 1.6 % percent approximately in the worst case. However, the robustness of the system is significantly increased.